Molecular dynamics algorithms: numerical and mathematical analysis
Appears in collection : On Future Synergies for Stochastic and Learning Algorithms / Sur les synergies futures autour des algorithmes d'apprentissage et stochastiques
We will present sampling algorithms which are used in computational statistical physics to sample multimodal measures and metastable dynamics. More precisely, we will focus on free energy adaptive biasing techniques to approximate thermodynamic quantities, and accelerated dynamics methods to sample the state-to-state dynamics of a metastable trajectory. The mathematical analysis of these algorithms relies on entropy techniques, and quasi-stationary distributions.
